We propose an entirely unsupervised approach for automatic segmentation of blood vessels to obtain the retinal vascular map. The significant contribution of this paper is to use top-hat transform followed by CLAHE for retinal image enhancement in preprocessing step. Use of top-hat transform facilitates to enhance only the blood vessels, simultaneously remove the local intensity change due to exudates, optic disc, and fovea from the background. For further image enhancement, CLAHE is applied on top-hat transformed retinal image. The preprocessed retinal image is passed through the Gabor filters bank, and the maximum outcome of the filters are chosen for each pixel. Otsu thresholding as global thresholding is applied to get a binary blood vessel structure. The proposed technique is proficient in identifying the blood vessels under uneven pigmentation and illuminance condition in the presence of exudates, optic disc, and fovea. Our proposed approach suppresses the non-vessel pixels in the preprocessing step, however multiscale Gabor wavelet filters efficiently represent the thick and thin vessels in the retinal image. The efficacy of the presented technique is validated on the publicly available Digital Retinal Image for Vessels Extraction (DRIVE) database [1]}.
